dc.creator | De La Vega, Gerardo, José | |
dc.creator | Corley, Juan Carlos | |
dc.date.accessioned | 2020-07-17T16:34:16Z | |
dc.date.accessioned | 2023-03-15T14:05:02Z | |
dc.date.available | 2020-07-17T16:34:16Z | |
dc.date.available | 2023-03-15T14:05:02Z | |
dc.date.created | 2020-07-17T16:34:16Z | |
dc.date.issued | 2019 | |
dc.identifier | 1366-5863 | |
dc.identifier | https://doi.org/10.1080/09670874.2018.1547460 | |
dc.identifier | http://hdl.handle.net/20.500.12123/7571 | |
dc.identifier | https://www.tandfonline.com/doi/abs/10.1080/09670874.2018.1547460 | |
dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/6210660 | |
dc.description.abstract | Spatial distributions models (SDM) are often used in invasive pest management to understand current and potential distribution. Using data on the well-studied spotted wing drosophila as a model, we compared distribution patterns of the range-limit with commonly
applied correlative and mechanistic models. Correlative models risk underestimation whereas simple mechanistic models provide overestimated range predictions, although using both approaches for the spotted wing drosophila improved range-limit predictions. Model choice when dealing with pests is central to the accurate identification of invasive species limit range and consequently for the deployment of monitoring and early detection programs. | |
dc.language | eng | |
dc.publisher | Taylor & Francis | |
dc.rights | info:eu-repo/semantics/restrictedAccess | |
dc.source | International Journal of Pest Management 65 (3) : 217-227 (2019) | |
dc.subject | Insecta | |
dc.subject | Drosophila | |
dc.subject | Especie Invasiva | |
dc.subject | Invasive Species | |
dc.title | Drosophila suzukii (Diptera: Drosophilidae) distribution modelling improves our understanding of pest range limits | |
dc.type | info:ar-repo/semantics/artículo | |
dc.type | info:eu-repo/semantics/article | |
dc.type | info:eu-repo/semantics/publishedVersion | |